Spatial patterns of snow distribution in the sub-Arctic
The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not...
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ftosti:oai:osti.gov:1924036 2023-07-30T04:00:48+02:00 Spatial patterns of snow distribution in the sub-Arctic Bennett, KE Miller, G Busey, R Chen, M Lathrop, ER Dann, JB Nutt, M Crumley, R Dillard, SL Dafflon, B Kumar, J Bolton, WR Wilson, CJ Iversen, CM Wullschleger, SD 2023-02-23 application/pdf http://www.osti.gov/servlets/purl/1924036 https://www.osti.gov/biblio/1924036 https://doi.org/10.5194/tc-16-3269-2022 unknown http://www.osti.gov/servlets/purl/1924036 https://www.osti.gov/biblio/1924036 https://doi.org/10.5194/tc-16-3269-2022 doi:10.5194/tc-16-3269-2022 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.5194/tc-16-3269-2022 2023-07-11T10:19:36Z The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017-2019; g1/4g2.5gkm2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (>g22g000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86g% of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe. Other/Unknown Material Arctic Seward Peninsula Alaska SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic The Cryosphere 16 8 3269 3293 |
institution |
Open Polar |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
spellingShingle |
54 ENVIRONMENTAL SCIENCES Bennett, KE Miller, G Busey, R Chen, M Lathrop, ER Dann, JB Nutt, M Crumley, R Dillard, SL Dafflon, B Kumar, J Bolton, WR Wilson, CJ Iversen, CM Wullschleger, SD Spatial patterns of snow distribution in the sub-Arctic |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017-2019; g1/4g2.5gkm2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (>g22g000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86g% of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe. |
author |
Bennett, KE Miller, G Busey, R Chen, M Lathrop, ER Dann, JB Nutt, M Crumley, R Dillard, SL Dafflon, B Kumar, J Bolton, WR Wilson, CJ Iversen, CM Wullschleger, SD |
author_facet |
Bennett, KE Miller, G Busey, R Chen, M Lathrop, ER Dann, JB Nutt, M Crumley, R Dillard, SL Dafflon, B Kumar, J Bolton, WR Wilson, CJ Iversen, CM Wullschleger, SD |
author_sort |
Bennett, KE |
title |
Spatial patterns of snow distribution in the sub-Arctic |
title_short |
Spatial patterns of snow distribution in the sub-Arctic |
title_full |
Spatial patterns of snow distribution in the sub-Arctic |
title_fullStr |
Spatial patterns of snow distribution in the sub-Arctic |
title_full_unstemmed |
Spatial patterns of snow distribution in the sub-Arctic |
title_sort |
spatial patterns of snow distribution in the sub-arctic |
publishDate |
2023 |
url |
http://www.osti.gov/servlets/purl/1924036 https://www.osti.gov/biblio/1924036 https://doi.org/10.5194/tc-16-3269-2022 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Seward Peninsula Alaska |
genre_facet |
Arctic Seward Peninsula Alaska |
op_relation |
http://www.osti.gov/servlets/purl/1924036 https://www.osti.gov/biblio/1924036 https://doi.org/10.5194/tc-16-3269-2022 doi:10.5194/tc-16-3269-2022 |
op_doi |
https://doi.org/10.5194/tc-16-3269-2022 |
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The Cryosphere |
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16 |
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3269 |
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3293 |
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